The paper analyses the use of voice assistants in people’s homes through the lens of activity theory guided by concepts such as mental models, context, the relationship between subject and tool as well as contradictions. Activity theory sees conversational devices including voice assistants not as ends in themselves, but as tools to aid the performance of a particular activity or practice. After a brief overview of the use of activity theory in HCI research, the empirical data gathered in an interdisciplinary project on the use of voice-enabled technology are discussed with a focus on the contradictions that have emerged in the course of our study. Contradictions have emerged with respect to the traditional view of home as private, which clashes with the fact that voice assistants may transmit personal data to external bodies. Another contradiction relates to the gulf between people’s expectations of smartness and the current shortcomings of commercial voice assistants. Finally, the paper presents suggestions for how one might design conversational technology in a way that helps resolve those contradictions and cope with the emerging phenomena such as autonomous agents.

Voice assistants have become embedded in people's private spaces and domestic lives where they gather enormous amounts of personal information which is why they evoke serious privacy concerns. The paper reports the findings from a mixed-method study with 65 digital natives, their attitudes to privacy and actual and intended behaviour in privacy-sensitive situations and contexts. It also presents their recommendations to governments or organisations with regard to protecting their data. The results show that the majority are concerned about privacy but are willing to disclose personal data if the benefits outweigh the risks. The prevailing attitude is one characterised by uncertainty about what happens with their data, powerlessness about controlling their use, mistrust in big tech companies and uneasiness about the lack of transparency. Few take steps to self-manage their privacy, but rely on the government to take measures at the political and regulatory level. The respondents, however, show scant awareness of existing or planned legislation such as the GDPR and the Digital Services Act, respectively. A few participants are anxious to defend the analogue world and limit digitalization in general which in their opinion only opens the gate to surveillance and misuse.

With the increasing proliferation of security-critical voice-based services such as voice banking, user authentication on smart speakers is becoming a vital requirement. Prior research on verifying the speaker’s identity has been taken a technical perspective predominantly, while respective user-centered research is scarce. To investigate authentication methods for smart speakers from a user’s perspective, we conducted a multi-method experiment. In a comprehensive online survey (n = 696) and a comparative lab study (n = 18) with an advanced functional prototype we studied 6 authentication methods (spoken PIN, biometrics, app with button/voice confirmation, card reader, sound authentication) regarding their perceived security and ease of use. While token-based authentication approaches (in particular an authenticator app on a smartphone) typically are perceived as more secure, they are found inferior when it comes to the ease of use. The currently most frequently used authentication method for smart speakers, the spoken PIN method, seems to represent a compromise between security and ease of use. The sophisticated sound authentication was appreciated for its ease of use, however, was rated worst regarding the perceived security.

Compared to parents of healthy children, parents of severely or chronically ill children have significantly worse physical and mental health and a lower quality of life, e.g. because of lack of sleep. The proposed solution aims at assisting caregivers by means of a remote monitoring service run by professional nursing staff which should allow parents to get a good night’s sleep. A smart algorithm has been developed to detect if a particular parameter (heart rate, respiration rate or oxygen saturation) has exceeded a pre-defined threshold and thus may imply an emergency. Parents are only alerted after a professional nurse in the monitoring centre has cross-checked vital parameter trends and carried out an audio-visual inspection. The quality and accuracy of the system has been validated through iterative testing including a test performed in a children’s hospital to ensure that the monitoring system is not inferior to a hospital set-up.

In a cross-national project, 14 neighborhoods from Germany, Austria and Switzerland were accompanied on their way to digitally supported neighborhood work. This paper discusses general requirements, choosing a suitable digital tool, the implementation process as well as the challenges faced by the various stakeholders. The following factors have been found to play a major role in sustainable neighborhood work: good fit with overall development strategy, interplay between online neighborhood work and physical interactions, strong existing neighborhood management structures, strategic planning of digitalization activities, start-up funding for innovation activities, and above all, the presence of a committed person or team as well as interesting content to attract users. Depending on the neighborhood, self-managed and individualistic solutions are preferred to generic and/or commercial solutions. There is no ‘fit-for-all’ path to sustainable digitally supported neighborhoods.

Verifying the identify of the speaker is a crucial requirement for security-critical voice-based services on smart speakers, such as transferring money or making online purchases. Whilst various studies have explored novel authentication mechanisms for voice-based services, there is little research on the user experience of respective authentication methods. To address this gap, we conducted a comprehensive online survey (n=696). We compared five authentication methods (spoken PIN, biometrics, app with button/voice confirmation, card reader) regarding their perceived efficiency, security, ease of use, and error susceptibility. Additionally, we investigated users' willingness to use security-critical services in banking and government. We found an overall preference to confirm actions triggered by voice by pressing a button on a mobile authentication app followed by PIN-based authentication. In contrast, biometric authentication by voice is considered unreliable, while applying a card reader is regarded secure, yet less convenient.

Digitalization is playing an increasingly significant role in practically all areas of society. The domain of healthcare has been moving into the digital world relatively late and only recently has started with digitalizing processes and services on a larger scale. Still, the potential for disruption in the healthcare industry is enormous. Although approaches to healthcare financing and regulatory schemes differ greatly between countries, it is generally recognized that current healthcare systems are characterized by lack of transparency and inefficiencies and that digitalization of healthcare services can lead to improvements in quality, efficiency and accessibility of care. We use the term “digital health” as an umbrella concept which subsumes eHealth, mobile or mHealth, telehealth or telemedicine, among others. Digital health can be defined as “an improvement in the way healthcare provision is conceived and delivered by healthcare providers through the use of information and communication technologies to monitor and improve the wellbeing and health of patients and to empower patients in the management of their health and that of their families” (Iyawa et al., 2016, p. 246). The COVID-19 pandemic, in particular, has shown how much can be gained if health data were stored and processed digitally. A smart information system could even lead to medical staff spending more time with patients and less on their PCs, for example, if information about patients were available seamlessly and the results of devices were transferred directly into their health records. Digitalization is actually a prerequisite of a patient-centered continuum of care model, which has been considered the gold standard by health experts for years. Further, digital health services are available independently of time and location, encourage the empowerment of patients and enable shared decision-making. But although the benefits of digital health services such as better accessibility of care are widely recognized, there has been no largescale integration into regular healthcare delivery. Rather, there is an abundance of successful pilot projects, which fail to be introduced into the regular healthcare delivery systems, i.e. the so-called ‘first healthcare market’, which includes reimbursable products, medicines and services. We assume that this discrepancy between expected benefits and actual implementation is primarily due to the lack of viable business models. Such business models play an important role in establishing sustainable service platforms and promoting the uptake of digital health services by health providers and patients. The healthcare market is characterized by a complex multi-stakeholder environment, fragmented decision-making processes as well as a lack of incentives for cost-effectiveness (see e.g. Botti & Monda, 2020). Besides, healthcare products and services are heavily regulated. The motto “Move fast and break things”, which tech companies use to describe the world as a playground for their creativity, does not fit hospitals. No advertising promise can be made without hard scientific evidence. Engineers in tech companies, on the other hand, are used to launching products early and then adjusting or stopping them. In medical technology, such an approach to product development would be unthinkable. Moreover, the development process has to be documented from the beginning according to official guidelines. There are two main routes into the healthcare market for tech firms: 1) doing business with hospitals and healthcare This is the Preface of the Topical Collection "Digital Healthcare Services".

Der digitale Wandel führt zu mehr Flexibilisierung, welche sich auch auf das betriebliche Gesundheitsmanagement (BGM) auswirkt. Die Arbeitswelt 4.0 birgt Chancen wie mehr Selbstbestimmung und bessere Vereinbarkeit von Beruf und Familie, aber auch Risiken wie psychische Überlastung und interessierte Selbstgefährdung, besonders in Organisationen mit indirekter Steuerung. Digitale Lösungen können eine wichtige Rolle bei der Stressbewältigung spielen und klassische BGM-Maßnahmen ergänzen.

The paper describes the design rationales and algorithms underlying SmartCoping, a mobile solution for recognizing stress based on the continuous monitoring of heart rate variability (HRV). A central contribution is the calibration of HRV values to each user of the SmartCoping app. Calibration is crucial since HRV varies greatly among people and must be interpreted individually. Calibration is implemented in two variants, one which requires user feedbacks on perceived stress levels during an initial learning phase and one where no feedback is needed, and a user’s maximal and minimal HRV values are determined during an initial usage phase. The variant with user feedbacks results in stress warnings which better reflect a user’s stress perception. The app can be used to trigger stress warnings, identify recurrent stress situations from the history data, and give relaxation support via a biofeedback component based on breathing exercises. SmartCoping helps people improve their self-perception and develop appropriate stress avoidance and coping strategies. The system has been evaluated in a field test with healthy volunteers.

Despite the promises of artificial intelligence (AI) technology, its adoption in medicine has met with formidable obstacles due to the inherent opaqueness of the internal decision processes that are based on models which are difficult or even impossible to understand. In particular, the increasing usage of (deep) neural nets and the resulting black-box algorithms has led to wide-spread demands for explainability. Apart from discussing how explainability might be achieved, the paper also looks at other approaches at building trust such as certification or controlling bias. Trust is a crucial prerequisite for the use and acceptance of AI systems in the medical domain.

Scientists promote the fostering of caring communities as a means of sustainably coping with demographic changes. They consider community-based technologies to have a high potential for supporting the establishment of caring communities. However, implementing community-based technologies is a complex endeavor, making sustainable adoption difficult. We have developed a maturity model aimed at standardizing the monitoring and evaluation of neighborhood projects. Based on a maturity model for integrated care, we conducted a Delphi study, to develop a maturity model for information and communication technology (ICT)-supported neighborhood development. In eight case studies, the model was validated and subsequently adapted to the specific needs and requirements of neighborhood projects. These studies emphasized the importance of at least 12 decisive dimensions and showed that the maturity model could be applied at different stages of a project. The current form of the maturity model can be used to help orient, as well as monitor and evaluate, neighborhood development projects. Future work will be necessary to further develop accompanying materials and services and to foster the exchange of best practices and experience between projects.

This paper introduces an alternative approach to conventional pedometer apps which measure the wide-spread goal of 10,000 steps a day. Instead we focus on the intensity of physical activity, which is in line with recent recommendations of renowned health institutions such as the WHO. These promote a minimum of moderate to vigorous physically active time per week to achieve the desired health benefits. The paper discusses how the guidelines have been implemented. It also outlines how we help maintain user motivation over time (e.g. by integrating and personalising "nudges") and how we intend to solve the challenges posed by different fitness levels and personal lifestyles.

BACKGROUND:Most people wish to die at home, but most people in Switzerland die in hospitals or nursing homes. Family caregivers often offer support so patients with palliative care needs can stay at home for as long as possible. However, crises and unplanned hospital admissions often occur in this setting because of family caregiver strain and symptom severity in patients. The so-called smart devices such as wearables or smartphones offer the opportunity to continuously monitor certain parameters and recording symptom deteriorations. By providing professionals with this information in a timely manner, crises in the home could be avoided.OBJECTIVE:The aim of this interdisciplinary study is to explore the symptom burden of people with palliative care needs who are cared for at home and to understand the development of crises in the home care setting. On the basis of the findings from this study, we will develop an early warning system to stabilize the home care situation and to prevent critical events from happening, thereby reducing avoidable hospitalizations.METHODS:A mixed method study is being conducted consisting of 4 main consecutive phases: (1) developing the monitoring system; (2) pretesting the system and adapting it to user needs; (3) conducting the study in the palliative home care setting with approximately 40 patients; and (4) distinguishing symptom patterns from the collected data specific to crisis emergence, followed by the development of an early warning system to prevent such crises. In study phase 3, each patient will receive an upper arm sensor and a symptom diary to assess symptom burden related to patients and family caregivers. A within-case analysis will be conducted for each patient's situation followed by a cross-case comparison to identify certain symptom patterns that may predict symptom deterioration (study phase 4).RESULTS:The collaboration with the local mobile palliative care team for participant recruitment and data collection has been established. Recruitment is forthcoming.CONCLUSIONS:We expect the findings of this study to provide holistic insight into symptom burden and the well-being of patients with palliative care needs and of their family caregivers. This information will be used to develop an early warning system to avoid the occurrence of potential crises, thereby improving palliative care provision at home.INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID):PRR1-10.2196/13933.

The journal The Lancet recently published a countdown on health and climate change. Attention was focused solely on humans. However, animals, including wildlife, livestock and pets, may also be impacted by climate change. Complementary to the high relevance of awareness rising for protecting humans against climate change, here we present a One Health approach, which aims at the simultaneous protection of humans, animals and the environment from climate change impacts (climate change adaptation). We postulate that integrated approaches save human and animal lives and reduce costs when compared to public and animal health sectors working separately. A One Health approach to climate change adaptation may significantly contribute to food security with emphasis on animal source foods, extensive livestock systems, particularly ruminant livestock, environmental sanitation, and steps towards regional and global integrated syndromic surveillance and response systems. The cost of outbreaks of emerging vector-borne zoonotic pathogens may be much lower if they are detected early in the vector or in livestock rather than later in humans. Therefore, integrated community-based surveillance of zoonoses is a promising avenue to reduce health effects of climate change.

The paper presents results from the SmartSleep project which aims at developing a smartphone app that gives users individual advice on how to change their behaviour to improve their sleep. The advice is generated by identifying correlations between behaviour during the day and sleep architecture. To this end, the project addressed two sub-tasks: detecting a user’s daytime behaviour and recognising sleep stages in an everyday setting. In the case of daytime activity detection the best results were achieved using an accelerometer at the wrist and another one at the ankle (87%). A subsequent smoothing step increased the accuracy to over 90%. For recognising sleep architecture we experimented with various consumer wearables that we used in addition to the usual PSG sensors in a sleep lab. Several sleep stage classifiers were learned from the resulting sensor data streams segmented into labelled sleep stages of 30 s each. Apart from handcrafted features we experimented with unsupervised feature learning based on the deep learning paradigm. Our best results for correctly classified sleep stages are between 86 and 90% for Wake, REM, N2 and N3, while the best recognition rate for N1 is 37%. Finally, we discuss a preliminary design of the algorithm for determining correlations between daytime behaviour and sleep architecture.